Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Sandra De Iaco"'
Publikováno v:
Entropy, Vol 25, Iss 7, p 1104 (2023)
Nowadays, various fields in environmental sciences require the availability of appropriate techniques to exploit the information given by multivariate spatial or spatio-temporal observations. In particular, radon flux data which are of high interest
Externí odkaz:
https://doaj.org/article/d00ffc0845c64a4d91c80e0c0ca4078a
Publikováno v:
Journal of Statistical Software, Vol 94, Iss 1, Pp 1-42 (2020)
Although a very rich list of classes of space-time covariance functions exists, specific tools for selecting the appropriate class for a given data set are needed. Thus, the main topic of this paper is to present the new R package, covatest, which ca
Externí odkaz:
https://doaj.org/article/32c919c7774041e29b7c552a4d0dd3a3
Autor:
Sandra de Iaco
Publikováno v:
Journal of Statistical Software, Vol 79, Iss 1, Pp 1-32 (2017)
Given a vectorial data set in two dimensions, a representation on a complex domain is often convenient. This representation is rarely considered in geostatistics, although interesting applications can be found in environmental sciences and meteorolog
Externí odkaz:
https://doaj.org/article/1fa2e1d7343246338911509ac45f0985
In environmental sciences, it is common to collect and analyze spatio-temporal multivariate data concerning several variables which are measured in time over a spatial domain. The spatio-temporal data are usually sparce in space, due to the high cost
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94546cb2ecc5852ee1454d87ef934c36
https://doi.org/10.5194/egusphere-egu23-16194
https://doi.org/10.5194/egusphere-egu23-16194
Groundwater over-exploitation and environment pollution, together with rising temperatures and other climate changes, can cause a large imbalance in the soil physicochemical properties, with a negative impact on economic, social and human health cond
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9c018118b5ef310e75bcab57b6df312
https://doi.org/10.5194/egusphere-egu23-14743
https://doi.org/10.5194/egusphere-egu23-14743
Autor:
Sandra De Iaco
Publikováno v:
Environmetrics. 34
With advances in modern worlds technology, huge datasets that show dependencies in space as well as in time occur frequently in practice. As an example, several monitoring stations at different geographical locations track hourly concentration measur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e2f9e5de0e9a5ad23afba3abb31a35c
http://urn.fi/URN:NBN:fi:jyu-202301191398
http://urn.fi/URN:NBN:fi:jyu-202301191398
Publikováno v:
Mathematical Geosciences. 54:459-465
Recent years have seen a steady growth in the number of papers that apply machine learning methods to problems in the earth sciences. Although they have different origins, machine learning and geostatistics share concepts and methods. For example, th
Autor:
Sandra De Iaco
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 36:2769-2787
In the literature, the theory of complex-valued random fields is usually recalled to describe the evolution of vector data in space, without including the temporal dimension. However, as in the real case, the development of the complex formalism in a
Autor:
Sandra De Iaco
Publikováno v:
Computational Statistics & Data Analysis. 183:107709